Abstract To build Video Question Answering (VideoQA) systems capable of assisting
humans in daily activities, seeking answers from long-form videos with diverse and complex …

Using machine learning to solve combinatorial optimization (CO) problems is challenging,
especially when the data is unlabeled. This work proposes an unsupervised learning …

Phylogenetic inference, grounded in molecular evolution models, is essential for
understanding the evolutionary relationships in biological data. Accounting for the …

We introduce a differentiable clustering method based on stochastic perturbations of
minimum-weight spanning forests. This allows us to include clustering in end-to-end …

Subset selection, ie, finding a bunch of items from a collection to achieve specific goals, has
wide applications in information retrieval, statistics, and machine learning. To implement an …

Symbolic regression (SR) has emerged as a pivotal technique for uncovering the intrinsic
information within data and enhancing the interpretability of AI models. However, current …

As illustrated in the main paper, MIST calculates multimodal attention between
segment/patch features and question features, then performs top-k hard selection over …

Multiple techniques have been proposed to extract multi-resolution representations (MRR)
from graphs in Graph Representation Learning (GRL). Graph Neural Networks (GNN) …

We introduce a differentiable clustering method based on stochastic perturbations of
minimum-weight spanning forests. This allows us to include clustering in end-to-end …

We consider a class of structured learning problems on arborescence (ie, the directed
spanning tree) from the input graph. The key step involved in this problem is predicting the …